diff --git a/previews/PR92/.documenter-siteinfo.json b/previews/PR92/.documenter-siteinfo.json index 1b382b6..51efe59 100644 --- a/previews/PR92/.documenter-siteinfo.json +++ b/previews/PR92/.documenter-siteinfo.json @@ -1 +1 @@ -{"documenter":{"julia_version":"1.9.3","generation_timestamp":"2023-10-27T09:38:12","documenter_version":"1.1.2"}} \ No newline at end of file +{"documenter":{"julia_version":"1.9.3","generation_timestamp":"2023-10-27T09:38:26","documenter_version":"1.1.2"}} \ No newline at end of file diff --git a/previews/PR92/api/index.html b/previews/PR92/api/index.html index bee626a..4a0dd9d 100644 --- a/previews/PR92/api/index.html +++ b/previews/PR92/api/index.html @@ -5,5 +5,5 @@ Other allowed proposals are

p1 = StaticProposal(Normal(0,1)) p2 = StaticProposal([Normal(0,1), InverseGamma(2,3)]) p3 = StaticProposal((a=Normal(0,1), b=InverseGamma(2,3))) p4 = StaticProposal((x=1.0) -> Normal(x, 1))


 The sampler is constructed using
-

julia spl = MetropolisHastings(proposal) ```

When using MetropolisHastings with the function sample, the following keyword arguments are allowed:

none is given, the initial parameters will be drawn from the sampler's proposals.

used if chain_type=Chains.

types are chain_type=Chains if MCMCChains is imported, or chain_type=StructArray if StructArrays is imported.

source

Functions

AdvancedMH.DensityModelType
DensityModel{F} <: AbstractModel

DensityModel wraps around a self-contained log-liklihood function logdensity.

Example:

l(x) = logpdf(Normal(), x)
-DensityModel(l)
source
+

julia spl = MetropolisHastings(proposal) ```

When using MetropolisHastings with the function sample, the following keyword arguments are allowed:

none is given, the initial parameters will be drawn from the sampler's proposals.

used if chain_type=Chains.

types are chain_type=Chains if MCMCChains is imported, or chain_type=StructArray if StructArrays is imported.

source

Functions

AdvancedMH.DensityModelType
DensityModel{F} <: AbstractModel

DensityModel wraps around a self-contained log-liklihood function logdensity.

Example:

l(x) = logpdf(Normal(), x)
+DensityModel(l)
source